Accurate information on accidents and on the relevant factors that affect them is critical for establishing the relationship between accident frequency and explanatory factors. In this study, we present a simplified method to extract road geometric features accurately from very high-resolution laser scanning data to analyze accident frequency on the North-South Expressway in Malaysia. Using expressway geometric features (i.e. horizontal and vertical alignments) extracted from laser scanning data and accident histories, this research first developed an APM based on geometric regression and a geographic information system (GIS). Then, an elasticity analysis was conducted to investigate the relationship between accident occurrence and road geometric design features. Results of the case study showed that the length of the road segments (mean D 0.014, elasticity D 0.122), the number of vertical curves in a road section (mean D 4.797, elasticity D 0.999), and the presence of a horizontal curve in a road segment (mean D 2.746, elasticity D 0.877), the average distance to the nearest access point (mean D-0.001, elasticity D ¡0.035), and AADT (mean D 3.01, elasticity D 0.881) determined accident occurrence, all at a significance level of 5%. This study shows that laser scanning systems can provide an easy and efficient method to collect transportation data, particularly those for accident analysis.